Distributed Resource Allocation for Cognitive Radio Network with Imperfect Spectrum Sensing

In this paper, we investigate the resource allocation problem for the scenario where a satellite based primary network and an orthogonal frequency division multiplexing (OFDM) based multiuser cognitive radio (CR) secondary network coexist. The resource allocation aims to maximize the throughput of CR users, and we develop a resource allocation algorithm based on game theory, which seeks to improve the spectrum utilization in a distributed fashion under the constraints of the transmit power and symbol error rate limits of CR users. The primary user interference and spectrum sensing errors are also taken into consideration. A gradient projection based algorithm is used to solve the distributed game and a compressive sensing technique is used to acquire the channel and interference parameters needed for resource allocation. Simulation results show that although implemented in a distributed way, the performances of the proposed algorithm are comparable to a centralized heuristic allocation method which represents the optimal allocation.